These teachings relate generally to power grid control, and, more particularly, to control of grid of Distributed Energy Resources.
The deployment of Distributed Energy Resources (DERs) is growing and has an impact on electric utility distribution networks. While DERs are increasing the volume of available energy resources with their multitude of benefits, further work is needed to assure successful management of a diverse and distributed energy mix.
The growing deployment of DERs leads to an electrical system that requires coordinated control functions that are more distributed than centralized. The growing deployment of DERs requires new energy markets operating at real-time supply and demand decision points.
Existing and emerging optimal power flow solutions, finding an operating point of the power system that minimizes a cost function, rely on information from both the utility operational control networks and information technology networks. In the traditional power grid the power flow problem is typically solved by centralized solvers that collect all the necessary field data, compute the optimal configuration, and dispatch the power production to the generators. However this approach is not practical in the distribution grids with distributed DERs, due to the frequent variability of the local grid conditions, to the poor prediction on distributed generators energy offer and consumer demand, and to the fact that generators can unexpectedly connect or disconnect. There is also cost, complexity, and dependency in relying on the utilities as monopolies to effectively execute unfavorable market based energy trade economy among DERs.
In order to cost-efficiently utilize large volumes and numbers of DERs on the existing grid infrastructure, the power grid needs to embrace new methods of grid control, capable of operating independently of utility operational systems.
Therefore, a solutions should not rely on data from the utility operational control networks, but only rely on data from the utility and/or non-utility information technology networks.